Streamlining business operations: the role of data in logistics management
The data your business collects can be of tremendous value, if it’s used in the right way. This goes especially for logistics operations, where marginal gains in efficiency can quickly accumulate to produce substantial advantages.
But where might these marginal gains be found?
The Importance of Data in Modern Logistics
Actionable data, in the world of logistics, might take many forms. It might take the form of traffic information, which might help a given shipment avoid congested routes as it deals with the last few miles. On the other hand, data might be used to predict demand on a given day of the week, and allocate essential resources, like drivers, accordingly.
Optimising Inventory Management with Real-Time Data
Warehousing is an essential consideration. If a given item is out of stock, or a warehouse is filled to capacity, then the business will ultimately lose money. Real-time data can be used to forecast demand for a given product, and send out orders for stock as required. Where this is done automatically, the costs of running a warehouse can be hugely reduced.
Improving Delivery and Route Optimisation
What method should a logistics company use to transport shipments? What routes should be preferred? The answers to these questions should ideally be driven by the highest-quality, most current data. This will drive down the cost of transport, and improve customer satisfaction.
Enhancing Supplier and Partner Collaboration Through Data Sharing
An effective logistics company doesn’t operate in isolation. Almost by definition, it does its work alongside suppliers and other partners. Sharing vital data with these organisations can help to improve outcomes for everyone, and keep the supply chain coordinated and effective. For example, if there’s going to be a disruption in the supply of a certain material, a supplier might advise the company so that contingencies can be made.
Data-Driven Decision-Making for Risk Management
Data might be a powerful means of assessing and anticipating risk. For example, it might be used to gauge how likely a disruption on the roads might be. Ideally, risk assessments should be conducted regularly – but a given piece of data might prompt an organisation to carry one out pre-emptively. This is something that a data analytics specialist from outside the company might be able to help with.
The Role of Data Analytics in Continuous Improvement
Data might not just be used to anticipate demand and deal with risk. It might also be used to troubleshoot. Data analytics might provide a clue as to where companies are going wrong, and what changes in procedures and equipment might yield gains in productivity. Key Performance Indicators might be used to assess the performance of an entire department, or an individual employee.
Ed Smith, online business and tech writer
